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1)  Grads segmentation
梯度分割
2)  gradient feature segmentation
梯度特征分割
1.
The method is based on the following three steps: first, Lee-filtering method is adopted to realize pre-filtering and noise reduction; this is followed by gradient feature segmentation, which separates the object area from the background area; finally the common linking method is adopted and the characteristic parameters of magnetic domain are calculated.
该方法采用如下三个步骤:首先,采用Lee滤波器进行预滤波和消除噪声;接下来进行梯度特征分割,将目标区域从背景中提取出来;最后对边缘进行连接并计算磁畴的特性参数。
3)  Gradient-based segme ntation
梯度图像分割
4)  gradient threshold value
梯度阈值分割
5)  segregate gradient effect
分割梯度效应
6)  Thiessen Tessellation
梯森分割
1.
Model of inventory and transportation based on Thiessen Tessellation;
基于梯森分割的库存运输模型
2.
Optimal Choosing for Urban Logistics Distribution Route Based on Thiessen Tessellation;
基于梯森分割的城市物流配送路线优化选择
3.
Study on Route Planning of Chain Enterprise Logistics Distribution Based on Thiessen Tessellation;
基于梯森分割的连锁企业物流配送路径规划研究
补充资料:梯度
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性质:设体系中某处的物理参数(如温度、速度、浓度等)为w,在与其垂直距离的dy处该参数为w+dw,则称为该物理参数的梯度,也即该物理参数的变化率。如果参数为速度、浓度或温度,则分别称为速度梯度、浓度梯度或温度梯度。

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